e-con Systems Expands Its Range of Camera Offerings

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e-con Systems Expands Camera Portfolio for Enhanced AI Vision

e-con Systems Expands Camera Portfolio Ahead of Embedded World 2025

Nuremberg, Germany – March 13, 2025 – e-con Systems®, a leader in embedded camera solutions, has announced an exciting expansion of its camera portfolio to enhance compatibility with the recently launched Renesas RZ/V2N processor. The new offerings will be showcased at Embedded World 2025 in Nuremberg, providing attendees a firsthand look at the latest in AI vision technology.

The company, which has a strong history of collaboration with Renesas, aims to bolster high-performance artificial intelligence capabilities across various industries, including industrial automation, smart surveillance, and robotics. At Renesas’ booth, visitors will experience an engaging AI vision demonstration featuring two innovative cameras: the e-CAM22_CURZH, a Full HD ultra-low light camera leveraging the Sony Starvis™ sensor, and the e-CAM25_CURZH, a Full HD Global Shutter Camera utilizing an onsemi® sensor. Both cameras are designed for seamless integration with the RZ/V2N development kit.

"We are thrilled to showcase our latest camera technology in conjunction with the RZ/V2N processor," stated Suresh Madhu, Head of Industrial Business Unit at e-con Systems. "With its outstanding AI capabilities, the RZ/V2N complements our camera solutions, enabling the development of advanced edge AI vision systems that perform remarkably well even in low-light scenarios."

Daryl Khoo, Vice President of the Embedded Processing Product Group at Renesas, echoed this excitement, stating, "The RZ/V2N is engineered for high-volume, broad-range vision AI solutions. Our ongoing collaboration with e-con Systems reinforces our commitment to delivering innovative solutions tailored to a variety of markets based on Renesas vision AI technologies."

As e-con Systems prepares for its showcase, the industry eagerly anticipates the transformative potential of these new camera solutions in advancing AI-driven applications.

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